Background: Cancer metastasis-related chemoresistance and tumour progression are the leading causes of death among CRC patients. Therefore, it is urgent to identify reliable novel biomarkers for predicting the metastasis of CRC.Methods: The gene expression and corresponding clinical data of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and multivariate analyses were performed to identify prognostic metastasis-related lncRNAs. Nomograms were constructed, and the predictive accuracy of the nomogram model was assessed by ROC curve analysis. Then, the R package “pRRophetic” was used to predict chemotherapeutic response in CRC patients. In addition, the CIBERSORT database was introduced to evaluate tumour infiltrating immune cells between the high—and low-risk groups. The potential roles of SNHG7 and ZEB1-AS1 in CRC cell lines were further confirmed by in vitro experiments.Results: An 8-lncRNA  signature was constructed for CRC prognosis prediction, which stratified patients into two risk groups. Kaplan-Meier analysis revealed that patients in the higher-risk group had a lower survival probability than those in the lower-risk group  The AUCs of 1-, 3-, and 5-year survival were 0.678, 0.669, and 0.72 in TCGA; 0.58, 0.55, and 0.56 in GSE39582; and 0.75, 0.54, and 0.56 in GSE29621, respectively. In addition, the risk score was an independent risk factor for CRC patients. Nomograms were constructed, and the predictive accuracy was assessed by ROC curve analysis. This signature could effectively predict the immune status and chemotherapy response in CRC patients. Moreover, SNHG7 and ZEB1-AS1 depletion significantly suppressed the colony formation, migration, and invasion of CRC cells in vitro.Conclusion: We constructed a signature that could predict the metastasis of CRC and provide certain theoretical guidance for novel therapeutic approaches for CRC. CRC is one of the most typical causes of cancer mortality and remains a challenging issue globally . Tumour LncRNAs comprise a large and diverse group of noncoding RNA transcripts longer than 200 nucleotides . AccumulIn the present study, we constructed an eight metastasis-associated lncRNA prognostic signature that may be a novel and independent prognostic factor of CRC patients based on TCGA dataset, and the predictive capacity was confirmed by the validation set . This signature could effectively predict the chemotherapy response in CRC patients.http://xena.ucsc.edu/). Patients without corresponding survival information were removed from further evaluation. We downloaded the raw “CEL” files and performed background adjustment and quantile normalization by a robust multiarray averaging method with the affy package. Based on the lncRNA information in the GENECODE data resource V22 (https://www.gencodegenes.org/), lncRNA expression profiles were extracted from the RNA-seq cohort. In the present study, TCGA-COAD (TCGA-Colon Adenocarcinoma) datasets and GEO datasets  were used for training and validation sets, respectively. The differential expression of lncRNAs between CRC and normal tissues from the GEO database was downloaded from LncRNA Explore (https://lncar.renlab.org/explorer).The workflow of this study is shown in http://www.broad.mit.edu/gsea/msigdb/)  (msigdb/) . Second,p value less than 0.05 was considered significant. Metastasis-related lncRNAs were subjected to univariate Cox regression assessment to identify those linked to CRC overall survival (OS). Only lncRNAs with statistical significance (p < 0.05) were enrolled in multiple stepwise regression analysis. A risk assessment model for the patients was then developed using multivariate regression coefficients of lncRNA expression. Thus, we generated the risk score by combining the expression value of the included lncRNAs weighted by the linear regression model coefficients.We performed univariate Cox regression to calculate the prognostic metastasis-related lncRNAs. A p < 0.05 was considered statistically significant. We also performed the same prognostic survival analysis in the validation cohort from GEO.The risk scores of CRC patients were calculated using the risk assessment model. The patients were assigned to a high- and a low-risk group, respectively, based on the cut-off values calculated by the survminer package in R. The Kaplan-Meier method was used to assess the efficiency of OS in high- and low-risk patients. A log-rank test p value less than 0.05 was considered statistically significant.We performed GO (gene ontology) enrichment analysis using the “clusterProfiler” R package to investigate the biological process differences between different risk groups. An adjusted The R package “pRRophetic” was used to predict chemotherapeutic response in CRC patients. The half-maximal inhibitory concentration (IC50) of the samples was calculated by ridge regression, and the prediction accuracy was assessed using 10-fold cross-validation based on the GDSC training set.To evaluate the proportions of tumour-infiltrating immune cells in the tumour microenvironment (TME), the CIBERSORT database was introduced to quantify the relative infiltration of immune cells in the TME. CIBERSORT includes molecular characterizations of 22 tumour-infiltrating immune subsets in cancer. We obtained significantly different immune cell types between high- and low-risk patients.2 and 5% CO2. Scrambled siRNAs were purchased from Shanghai GenePharma. Subsequently, cells were transfected with a Lipo3000 kit according to the manufacturer’s instructions.Cells were cultured in DMEM  with 10% FBS  in a humified atmosphere of 95% OCells were incubated in ice-cold lysis buffer containing phosphatase inhibitor and protease inhibitor cocktail for 20 min. The bicinchoninic acid (BCA) assay was used to detect protein concentration. Equal amounts of protein samples were separated by 4–12% SDS/PAGE and transferred to PVDF membranes. The membranes were blocked with 5% nonfat dry milk for 1 h and incubated with the corresponding primary antibodies , vimentin , E-cadherin , N-cadherin , AKT/p-AKT , ERK/p-ERK , and PI3K/p-PI3K  overnight at 4°C, followed by incubation with secondary antibodies for 1 h at room temperature. Immunoreactive protein levels were detected using an ECL western blotting kit.5 cells) were suspended in FBS-free medium and then seeded into the top chamber . Medium with 10% FBS was added in the lower chamber. After incubation for 24–36 h, the chambers were fixed and stained with crystal violet. Evaluation of migration capacity was performed by counting invading cells under a microscope. The invasion assay was performed similarly to the migration assay with the upper chamber coated with Matrigel .Cell migration and invasion were detected by Transwell methods. Cells  software and GraphPad Prism 8. All the results were presented as mean ± standard deviation (SD). The student’s t-test was performed to compare the differences between the two groups. Differences in survival between different risk groups were compared by Kaplan-Meier curves followed by a log-rank test. N = 448), GSE39582 (N = 585), and GSE29621 (N = 65), were integrated in our study for further analysis. The baseline information of all CRC datasets is summarized in p < 0.05), we finally obtained 840 metastasis-related lncRNAs (The workflow of this study is shown in  lncRNAs .p < 0.05) . Based on multiple stepwise regression analyses, we finally obtained eight lncRNAs, namely, LINC00261, RP1-170O19.17, CAPN10-AS1, SNHG7, ZEB1-AS1, U47924.27, NIFK-AS1, and LINC00925 (p < 0.05). In contrast, low LINC00261 expression predicted poor outcome in CRC (p < 0.05)  . Based INC00925 ; Table 2 < 0.05) . In addi < 0.05) , Table 3 < 0.05) . Then, t < 0.05) . The dis < 0.05) . To vali < 0.05) .p < 0.001). In multivariate Cox regression analyses, the risk score still proved to be an independent predictive factor for OS   . In addi< 0.001) . All theThen, we performed the Fagan nomogram to examine the clinical application of the 8-lncRNA signature. All variables that were significant  in the multivariate analysis are enumerated in the nomogram according to the algorithm. The variable scores were summed to give the total points, and the total point line is shown at the bottom of the nomogram, which can predict the probability of OS at 3 and 5 years . Subsequ+ T activated and lower macrophage M0 and macrophage M2 activated (p < 0.05) (To further explore the relationship between the prognostic model (risk score) and tumour-infiltrating immune-cell fractions, we quantified the enrichment scores of diverse immune cell subpopulations. The results demonstrated that compared to the high-risk group, patients in the low-risk group contained a higher proportion of memory CD8 < 0.05) . We furt < 0.05) . These rWe used the R package “pRRophetic” to estimate the response to chemotherapy drugs in the high- and low-risk groups. To investigate the potential biological functions and pathways associated with the risk signature, we performed GO and hallmark enrichment analyses between the high- and low-risk groups. Interestingly, as shown in To validate the effect of lncRNAs on CRC cells, we next performed RNA interference (RNAi) to deplete the expression of ZEB1-AS1 and SNHG7, and the transfection efficacy was then verified . A colonCell migration and invasion were evaluated by wound healing and Transwell assays. Wound healing analysis suggested that cell migration was significantly reduced after ZEB1-AS1 and SNHG7-siRNA transfection compared with the control group . TransweIn the enrichment analysis, we found that DEGs were significantly enriched in the PI3K/AKT pathways. This observation was further confirmed by WB analysis, which suggested that ZEB1-AS1 and SNHG7 knockdown significantly decreased the levels of phospho-Akt (p-AKT), phospho-PI3K (P-I3K) and phospho-ERK (p-ERK) . All theCRC is one of the most diagnosed malignancies and is considered a leading cause of cancer-related deaths worldwide . Cancer Undoubtedly, CRC patients with metastasis usually have a poor prognosis, with 5 years survival rates of less than 40% . Severalβ-catenin through inhibiting the activation of the Wnt pathway  macrophages and activated (M2) macrophages. In addition, we further performed GO analyses and unexpectedly found that several immune-related biological processes and pathways were enriched, which suggested that the 8-lncRNA metastasis signature may be a superior predictive determinant of tumour immune infiltration. CRC patients with tumour metastasis, especially distant metastasis, appear to be multidrug resistant to the current treatments  on the development and progression of cancer. Assessment of the enrichment of tumour infiltrates may help to predict the prognosis and host immune response to tumour antigens of CRC patients . In the eatments . Therefoeatments . TherefoNevertheless, there were several limitations in this study. Our study was conducted solely based on data from a public database, and the gene signature was identified mainly with retrospective datasets. Therefore, inherent case selection bias may have influenced the results. In addition, due to the limitation of the length of this paper, we only explored the expression of SNHG7 and ZEB1-AS1 and its biological functions in CRC, and the specific effect and mechanism of the other lncRNAs in CRC remain unclear. The expression profiles of the eight lncRNAs combined with clinical validation in the patients of the prospective cohort need to be further proven. These are relevant issues that will be explored further in follow-up research that will build on this initial study. More potential markers should be identified and incorporated into our prediction model in the future.in vitro experiments. Thus, the gene signature may serve as a novel biomarker with diagnostic and prognostic value for CRC patients.In summary, we systematically analysed the expression profiles and prognostic value of the metastasis-related signature in CRC and developed an eight metastasis-related signature for predicting the prognosis of CRC patients. The eight metastasis-related signature was proven to be an independent prognostic factor for patients with CRC. Then, the lncRNA risk prediction score was validated through two external validation cohort. Nomograms were constructed, and the predictive accuracy was assessed by ROC curve analysis. This signature could effectively predict the immune status and chemotherapy response in CRC patients. Moreover, the potential roles of SNHG7 and ZEB1-AS1 as metastasis drivers in CRC were confirmed by


Clinicians should be aware that subacute thyroiditis (SAT) might be an under-reported adverse effect of COVID-19 vaccines.In records from endocrinological examinations, we reviewed the incidence of diagnoses of SAT from 2000 to 2020 and during the 2021 COVID-19 vaccination campaign.Review of electronic records from June to December in each year from 2000 to 2021.From 2000 to 2020, 51 patients in our centre had SAT (0.6%). From June to December 2021, 7 females were diagnosed with SAT after vaccination. The percentage of SAT in 2021 medical files was 1.5%. SAT diagnoses significantly (P = 0.03) increased in 2021 in comparison with the 2000–2020 period. The median age of SAT patients in 2021  was higher than in the 2000–2020 period .To date, few cases of SAT after COVID-19 vaccinations have been described in the literature, with sub-clinical, normal or increased thyroid function during 1-3-month follow-up. Our findings indicate that SAT after COVID-19 vaccination occurs more frequently than in other virus-related cases and at a greater age. Our observation of a local increase in SAT during the 2021 COVID-19 vaccination campaign indicates that physicians should be aware of this infrequent side effect, which must be considered and monitored after COVID-19 vaccination. Subacute thyroiditis (SAT) due to viral infections is an infrequent cause of thyrotoxicosis . Common In the COVID-19 era, SAT seems to be an underestimated consequence of the disease which occurs during SARS-CoV-2 infection . We reviThe aim of this study was to compare the incidence of SAT in these two periods: before and during the 2021 COVID-19 vaccination campaign.The study was conducted in the private secondary Priamar Centre for out-patients. Electronic records of all endocrinological examinations from June to December in each year from 2000 to 2020 were searched. From 8115 medical files, 51 diagnoses of SAT were anonymously retrieved . In the corresponding period in 2021, in 466 medical files, SAT was diagnosed in 7 women after COVID-19 vaccination. The diagnosis was made according to the following findings: neck pain and tenderness on palpation, focal or diffuse hypoechogenicity and/or heterogeneous echostructure of the thyroid on ultrasonography (US), increased inflammatory makers [erythrocytesedimentation rate (ESR) and/or C-reactive protein (CRP)], and transient clinical signs of mild/moderate thyrotoxicosis. After the onset of illness, thyroid function tests  and thyroid autoimmunity  were carried out by means of commercial assays in the laboratory of Local Health Service 2 Savonese. Analytic normal ranges are: ESR < 25 mm/h, CPR < 5 mg/l, f-T4 12.0–22.0 pmol/l, TSH 0.3–4.2 mIU/l, TRAb < 0.7 mIU/l and TPOAb (negative according to the manufacturers). Non-parametric tests  were used. The study was approved by the Priamar Centre’s institutional board, and a waiver of informed consent was granted because the research involved no risk to patients.From 2000 to 2020, about 0.6% of the patients evaluated in our centre had SAT, which occurred at the median age of 45 years (IQR 38–52 years) with an incidence of 1–3/year. The long-term evolution of the disease was known in 25 cases (49%) and full thyroid recovery or chronic thyroiditis/hypothyroidism was observed in 72% and 28% of cases, respectively. From June to December 2021, 7 women were diagnosed with SAT after vaccination , although higher ages on SAT presentation have been reported , 8. SAT , althougIn conclusion, our observation of a local increase in SAT during the 2021 COVID-19 vaccination campaign indicates that physicians should be aware of this infrequent side effect, which must be considered and monitored after COVID-19 vaccination.


To our knowledge, no study has investigated whether the putative afterload dependence of the Ca2+ transient is preload dependent. This study is designed to provide the first insight into the Ca2+ handling of cardiac trabeculae undergoing work-loop contractions, with the aim to examine whether the conflicting afterload dependency of the Ca2+ transient can be accounted for by considering preload under isometric and physiological work-loop contractions. Thus, we subjected ex vivo rat right-ventricular trabeculae, loaded with the fluorescent dye Fura-2, to work-loop contractions over a wide range of afterloads at two preloads while measuring stress, length changes, and Ca2+ transients. Work-loop control was implemented with a real-time Windkessel model to mimic the contraction patterns of the heart in vivo. We extracted a range of metrics from the measured steady-state twitch stress and Ca2+ transients, including the amplitudes, time courses, rates of rise, and integrals. Results show that parameters of stress were afterload and preload dependent. In contrast, the parameters associated with Ca2+ transients displayed a mixed dependence on afterload and preload. Most notably, its time course was afterload dependent, an effect augmented at the greater preload. This study reveals that the afterload dependence of cardiac Ca2+ transients is modulated by preload, which brings the study of Ca2+ transients during isometric contractions into question when aiming to understand physiological Ca2+ handling.Preload and afterload dictate the dynamics of the cyclical work-loop contraction that the heart undergoes in vivo. Cellular CaNEW & NOTEWORTHY This study is the first examination of Ca2+ handling in trabeculae undergoing work-loop contractions. These data reveal that reducing preload diminishes the influence of afterload on the decay phase of the cardiac Ca2+ transient. This is significant as it reconciles inconsistencies in the literature regarding the influence of external loads on cardiac Ca2+ handling. Furthermore, these findings highlight discrepancies between Ca2+ handling during isometric and work-loop contractions in cardiac trabeculae operating at their optimal length. The heart in vivo undergoes a cyclical work-loop contraction pattern where the venous pressures upstream (preload) and arterial pressures downstream (afterload) dictate the pressure development and, therefore, the shortening and lengthening dynamics of ventricular muscle fibers. Over the past century, it has become apparent that cardiac stress-length mechanics are contraction mode dependent. For a given length, the isometric stress production is greater than the end-systolic stress produced at the end of the shortening phase in a work-loop, and this discrepancy is augmented at lower afterloads  but elim2+ transients, the primary driver of cardiac contraction, are commonly studied within isometric contractions, where an external load prevents isolated muscle fibers from shortening. No study has measured Ca2+ transients in cardiac trabeculae undergoing work-loop contractions. A handful of investigations, in both multicellular .wkZ) as follows. Briefly, the force generated by the muscle upon stimulation was scaled in the FPGA to an equivalent ventricular pressure using measured muscle dimensions and applying Laplace’s law , the Laplace domain expression of the arterial pressure stored in the vascular network. As in the heart, ejection/muscle shortening could only occur when ventricular pressure exceeded that of the arterial network. Once this condition was met, the flow rate of blood out of the ventricle was computed fromWkZ(s) is the Laplace-domain transfer function of a Windkessel model of the vasculature defined ascZ is the characteristic impedance, pR is the peripheral resistance, and C is the arterial compliance. Q(s) was then scaled into its one-dimensional equivalent (rate of shortening) and used to control the rate of length change of the muscle. The ejection phase continued until the arterial pressure exceeded the ventricular pressure, whereupon the trabecula relaxed isometrically. As the rate of stress change approached zero, the trabecula was restretched back to its initial length. The restretch rate was user defined by a constant volumetric refill rate and scaled into the equivalent muscle length.The muscle contracted isometrically until the pressure exceeded pR within the range from 5 kPa·s/mL to 1,000 kPa·s/mL, while C and cZ were held constant at 0.032 mL/kPa and 5 kPa·s/mL, respectively. These values were adapted from a previous study  before being injected with heparin . The rats were killed via cervical dislocation and their hearts removed within 30 s. Each excised heart was immediately submerged in ice-cold 2,3-butanedione monoxime (BDM)-Tyrode’s solution consisting of (in mM): 130 NaCl, 6 KCl, 1.5 MgCl2, 0.5 NaH2PO4, 0.3 CaCl2, 10 glucose, and 20 2,3-butanedione monoxime (BDM). The heart was then transferred to a dissection bath, and Langendorff perfused with the BDM-Tyrode’s solution at room temperature with the pH adjusted to 7.4. The atria were removed and the ventricles opened by cutting along the septum. Trabeculae used within this study were excised from the right ventricle.To obtain trabeculae, 8- to 10-wk-old male Wistar rats were anesthetized with gaseous isoflurane  to maintain the pH at 7.4 and supply the muscle with ample oxygen throughout the protocol. The stimulus frequency was set to 1 Hz throughout an hour-long equilibration period for the acclimatization of the trabecula.Each dissected trabecula was mounted between two platinum hooks in the cardiomyometer . Voice-c100L). A central window was imaged with a ×20 objective lens, and the average sarcomere length was calculated using a two-dimensional (2-D)-fast Fourier transform algorithm . During loading, the stimulation frequency was set to 0.2 Hz, and the muscle superfused with a loading solution comprised K-H solution with 10 μM of cell-permeable Fura-2/AM and 1 mM probenecid. Loading was considered complete when 365F had reached 10 times the background fluorescence measurement or the loading period had reached 2 h. Following loading, the superfusate was switched back to the standard K-H solution with 1 mM probenecid, and the stimulus frequency increased to 2 Hz. Intracellular Ca2+ dynamics were taken as 340/F380F.Fura-2 was used to measure intracellular CaoC) and the Fura-2 leak rate. At 37°C, the leak rate of Fura-2 is substantial even in the presence of probenecid (Following the achievement of a steady state of both stress production and the fluorescence ratio (unchanged diastolic and peak measurements over a 10-min period), the bath temperature was increased to 32°C using a thermoelectric heat pump in combination with a temperature controller. The experiment was performed at 32°C as a compromise between physiological temperature  and maximal (isometric) stress. The order in which pR values were used was randomized to mitigate the introduction of fatigue basis into the measurements. The muscle length was changed to 100L or 95L depending on the starting length, and the process was repeated until data for all afterloads had been collected. Force and Ca2+ data were collected for the duration of this protocol.After the temperature stabilized, the experiment commenced by setting the muscle to one of two preloads, achieved by setting the muscle length to either 100Lwith the trabecula at quiescence. In total, seven trabeculae were studied. Their cross-sectional area was measured using spectral-domain optical coherence tomography as described previously . From the OCT images, we approximated the major and minor diameters of the trabeculae that represented the way an experimentalist may have been able to measure using a microscope and an angled mirror. These major and minor diameters averaged 300 ± 100 µm and 260 ± 40 µm, respectively.At the end of the experiment, muscle geometry was measured at eviously . Brieflyeviously . After seviously . The sev2+ transient may be a consequence of motion artifacts, as has been considered previously  software and analyzed offline using a series of custom-written MATLAB (MathWorks) programs. Muscle-specific averages of 10 steady-state force twitches and Caxtracted . Data woxtracted . HoweverMuscle force was converted to stress using the measured cross-sectional area. Active twitch stress under the isometric contraction was revealed by subtracting the constant passive force from the total twitch stress A. For wodS/dt), and various twitch durations . The twitch durations represent the time that stress remained greater than X % of active stress, where X is the subscript number . Equivalent parameters were extracted to analyze the Ca2+ dynamics in the form of 340/F380F time integral (CTI), maximum rate of 340/F380F rise (340/F380/dtdF), and transient durations . In addition, various decay timings , time to peak (peakt), diastolic, peak, and 340/F380F amplitude were calculated. The decay timings represent the time the Ca2+ signal takes to decay by X % from the peak . With the exception of the rate of rise of stress and 340F/380F, all parameters are illustrated in The dynamics of stress were analyzed using the following parameters: stress-time integral (STI), maximum rate of stress development (These parameters were plotted against relative end-systolic stress (ESS). ESS was defined as the stress at the time point where muscle length stopped reducing at the end of the shortening phase and represents the afterload experienced by the muscle. This was expressed relative to the isometric stress of the associated initial length. Hence, relative ESS was equal to 1 for isometric contractions.F test was performed for each parameter to determine whether a first- or second-order polynomial was sufficient to describe the relationship. The relationship included the parameters pertaining to twitch stress, and those pertaining to the Ca2+ transient, as functions of relative ESS. Statistical regression between the independent and dependent variables was performed using SAS software (Copyright 2021 SAS Institute Inc.). Linear mixed-effect models in SAS were used with muscle number treated as a random effect, and the initial muscle length (preload) and relative ESS (afterload) treated as fixed effects. A compound symmetry covariance structure was used in the model statement as this corresponded with the model with the smallest Akaike information criterion value. Afterload dependence was considered significant for each preload if the P value associated with either the linear term or, when applicable, the quadratic term, in the fixed effect between independent and dependent variables was <0.05. The effect of preload was considered significant if the P value associated with the “Contrast” statement in SAS output between the two regression lines for 100L and 95L was <0.05.An 2+ handling of cardiac muscle during isometric  than those at 95L .The stress, length, and ransient C and G.  preload C. A secoractions C and G aractions G. The isdur75, tdur50, tdur25t, and dur10t) increased with increasing afterload  reached a plateau at higher afterloads . It is worth noting that the time at which dS/dt occurred always preceded the commencement of shortening in work-loop contractions.fterload A–D. The r tdur50 B and tdu , peak, diastolic, amplitude, or the maximum rate of rise of the 340/F380F signal  were plotted in 100L, afterload dependence was obtained at the three earlier decay timings  were adapted from a previous study  during relaxation at a faster rate than it can be sequestered into the sarcoplasmic reticulum (SR)  of the twitch stress increased. As expected, 50t, which aligns approximately with the bump onset, decreased with increasing afterload, reflecting the delayed bump onset. Further, 75t, which aligns with the bump region, was longer with increasing afterload, reflecting the enhanced bump amplitude. The final metric of the Ca2+ decay, 90t, is not afterload dependent, and thus it appears that the afterload-induced TnC binding affinity does not affect the overall decay phase of the Ca2+ transient.The plateau in the Ca studies , 46, 47  studies . The bum2+ transient afterload dependency. We found that the decay-related timing metrics 50t, 75t, and 90t had preload-informed modulation of their afterload dependency. The underlying molecular basis for this warrants further study, but we speculate that it too can be explained by the force-dependent Ca2+-TnC cooperativity. This speculation stems from two of our findings. First, the preload was more influential on the overall duration of the Ca2+ transient than afterload, as 90t and dur10t (Ca2+) were shorter at the lower preload while being afterload independent , which provides an insight into the exposure of internal structures to Ca2+, was independent of afterload and preload . When the muscle shortens during contractions, the affinity for Ca2+ decreases and causes some Ca2+ to unbind from TnC and “slow” the Ca2+ transient decay  are too low for the binding reaction of Fura-2 and Ca2+ to be at equilibrium during a Ca2+ transient  and 95L, it is difficult to extrapolate the afterload dependence to even lower preloads. At muscle lengths shorter than 85L, we have observed that work-loop contractions result in out-of-plane motion where the distance between the trabecula and the microscope objective varied. To avoid this out-of-plane motion confounding the fluorescence signals, we limited the shortest muscle length to 95L as the muscle shortening was ∼10% of the initial muscle length at the lowest afterload , Sir Charles Hercus Health Research Fellowships (20/011 and 21/116) from the Health Research Council of New Zealand , a Doctoral Scholarship awarded by the Heart Foundation of New Zealand (awarded to A.A.), Marsden Fast-Start grants (UOA1504 and UOA1703) from the Royal Society of New Zealand , and a James Cook Research Fellowship from the Royal Society of New Zealand (awarded to A.J.T.). The original development of this instrument was funded by a Marsden grant (11-UOA-199) from the Royal Society of New Zealand (awarded to A.J.T. and P.M.F.N.).No conflicts of interest, financial or otherwise, are declared by the authors.J.M.D., K.T., A.S.G., A.J.A., P.M.F.N., A.J.T., and J-C.H. conceived and designed research; J.M.D. performed experiments; J.M.D. and J-C.H. analyzed data; J.M.D. interpreted results of experiments; J.M.D. prepared figures; J.M.D. drafted manuscript; J.M.D., K.T., A.S.G., A.J.A., P.M.F.N., A.J.T., and J-C.H. edited and revised manuscript; J.M.D., K.T., A.S.G., A.J.A., P.M.F.N., A.J.T., and J-C.H. approved final version of manuscript.


Porphyromonas gingivalis and Tannerella forsythia, synthesize ceramide phosphoethanolamine (CPE) species, membrane sphingolipids not typically found in vertebrates. Previously, it was shown that this particular lipid can be specifically detected by an aegerolysin protein, erylysin A (EryA). Here, we show that EryA can specifically bind to CPE species from the total lipid extract from P. gingivalis. Furthermore, using a fluorescently labelled EryA-mCherry, we were able to detect CPE species in clinical samples of dental plaque from periodontal patients. These results demonstrate the potential of specific periodontal pathogen-derived lipids as biomarkers for periodontal disease and other chronic inflammatory diseases.Periodontal disease is a chronic oral inflammatory disorder initiated by pathobiontic bacteria found in dental plaques—complex biofilms on the tooth surface. The disease begins as an acute local inflammation of the gingival tissue (gingivitis) and can progress to periodontitis, which eventually leads to the formation of periodontal pockets and ultimately results in tooth loss. The main problem in periodontology is that the diagnosis is based on the assessment of the already obvious tissue damage. Therefore, it is necessary to improve the current diagnostics used to assess periodontal disease. Using lipidomic analyses, we show that both crucial periodontal pathogens,  Porphyromonas gingivalis, Tannerella forsythia, Aggregatibacter actinomycetemcomitans, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, and some others [Periodontal disease is of great importance worldwide, affecting more than 10% of the adult population ,3 and ale others ,10.The standard diagnostic procedure in periodontology is usually based on clinical measurements, such as probing pocket depth, clinical attachment level, and bleeding on probing, supported by radiographic evaluation . As patiCeramide phosphoethanolamine (CPE) is a major sphingolipid in the cell membranes of arthropods ,32,33 anPleurotus sp.). Aegerolysins  are small (13–20 kDa) acidic proteins that have been identified in several eukaryotes and prokaryotes and are particularly abundant in bacteria and mushrooms [Dk~1 nM) to sphingomyelin (SM)/cholesterol (Chol)-enriched membranes [Dk~1 nM) to membranes containing equimolar amounts of CPE and Chol [Since CPE is present in periodontal pathogens it could represent a potential molecule for the diagnosis of periodontal disease and the determination of its severity. The question of how to detect CPE can be addressed using a protein from the aegerolysin family of edible oyster mushrooms A is a 15 kDa protein produced by ith Chol ,53. It cith Chol ,54. Sinc tissues . In addiPleurotus aegerolysins can act in concert with proteins that have a membrane-attack-complex/perforin (MACPF) domain and are also produced by Pleurotus mushrooms [Moreover, ushrooms ,56,57. Aushrooms . It has ushrooms ,58. Evenushrooms .Based on its specific interactions with CPE, we assumed that EryA might bind to CPE and its forms, such as DH-CPE, produced by periodontal bacteria. Therefore, the aim of this study was to test whether fluorescently labelled EryA could be used as a diagnostic tool to detect CPE species and for monitoring periodontal disease.sn-glycero-3-phosphocholine (POPC) and porcine brain SM were from Avanti Polar Lipids  and CPE from Matreya . Lipids were dissolved in chloroform or in the case of CPE, in chloroform/methanol  and stored at −20 °C prior to use.Unless specified otherwise, all chemicals used in the study were from Sigma-Aldrich . Cholesterol, 1-palmitoyl-2-oleoyl-Porphyromonas gingivalis ATCC 33277, Tannerella forsythia DSM 102835, and Aggregatibacter actinomycetecomitans DO15 were provided by prof. Katja Seme from the Institute of microbiology and immunology, Faculty of Medicine, University of Ljubljana, Slovenia. As negative control Escherichia coli DH5α was used. All bacteria were maintained for 3–5 days at 37 °C in different growth conditions: P. gingivalis on 5% horse blood agar plates supplemented with 5 mg/L hemin and 1 mg/L menadione in an anaerobic atmosphere; T. forsythia on a tryptic soy agar containing 0.001% N-acetylmuramic acid in an anaerobic atmosphere; A. actinomycetecomitans on a tryptic soy-serum-bacitracin-vancomycin agar in air +5% CO2; and E. coli on Luria-Bertani agar in an aerobic atmosphere prior to use.Recombinant proteins EryA, fluorescently-tagged EryA-mCherry and PlyB were produced as described previously ,56. ProtP. gingivalis, T. forsythia, A. actinomycetemcomitans, and E. coli was performed according to the protocol of Bligh and Dyer [2O and 4 mL of chloroform/methanol  were added. The mixture was vortexed and left to sit for 2 h at 25 °C. Chloroform (1.5 mL) and a mixture composed of 2 M KCl and 0.5 M K2HPO4 (1.5 mL) were then added and vortexed. The solution was centrifuged at 2000× g for 10 min to induce the separation of the upper aqueous phase and the lower lipophilic phase. The lower phase was left to evaporate, and the dried lipids were then dissolved in hexane/isopropanol/dH2O , vortexed, and centrifuged at 2000× g for 10 min. The upper phase was separated from the pelleted protein impurities, dried under nitrogen, and stored at −20 °C. Before use, the remaining lipids were dissolved in chloroform/methanol  and stored at −20 °C.Extraction of total lipids from bacteria and Dyer  with modand Dyer . The pel1H-NMR (400 MHz) spectra of P. gingivalis lipid extract were recorded in MeOH-d4 at 300 K on a nuclear magnetic resonance (NMR) spectrometer , with a 5-mm double resonance broadband probe equipped with a pulsed-gradient field utility. The 1H-90° proton pulse length was 9.3 µs, with a transmission power of 0 db. The probe temperature was maintained at 300.0 K (±0.1 K) using a variable temperature unit . Calibration of the chemical shift scale (δ) for 1H and 13C nuclei was obtained on the residual proton signal of the MeOH-d4 at δH 3.310 and δC 49.00 ppm, respectively. We obtained 1H-NMR . The resulting 1D and 2D-NMR spectra were analysed using TopSpin 3.6.1 . The lipid classes from the NMR data were identified through comparisons with our previous NMR measurements carried on commercially available lipid standards.The details of the transitions used in the multiple reaction monitoring (MRM) experiments are provided in 18 column . The solvent system consisted of eluent A as MeOH/H2O  containing 10 mM ammonium acetate and eluent B as isopropanol/MeOH  containing 10 mM ammonium acetate. Samples were resuspended in 1 mL CHCl3/MeOH , and 10 µL was run with a linear gradient from 65% eluent B to 100% B in 40 min, plus 20 min isocratic 100% B at 1 mL/min, to elute the diglycerides and triglycerides. The column was then equilibrated to 65% B for 10 min. The MS scan range was 13,000 U/s in the range of 50 to 1500 m/z, with a mass accuracy of ~100 ppm. The nebulizer gas was high purity nitrogen at a pressure of 20 to 30 psi, at a flow rate of 6 L/min, and at 300 °C. The electrospray ionization was operated in positive ion mode for the qualitative and quantitative analyses of phosphatidylcholine (PC), lyso-PC, and SM, and in both positive and negative ion modes for phosphatidylinositol (PI), phosphatidylethanolamine (PE), CPE, and DH-CPE. For the structural assignments of the lipid species, the extracted ion chromatograms from the positive and/or negative ion full scan data were integrated using the DataAnalysis 3.0 software . Ceramide analyses were performed by multiple reaction monitoring (MRM) using a triple quadrupole mass spectrometer  coupled to an HPLC system . Detailed parameters on transitions and collision energies are reported in the The lipid extract was analysed by liquid chromatography-mass spectrometry (LC-MS)  coupled to a quadrupole ion-trap mass spectrometer  equipped with an electrospray ionization source and in both positive and negative ion modes. Chromatographic separation of lipids was carried out at 303 K on a thermostated Cn = 20) aged 21–25 years with good oral hygiene and no gingival inflammation or systemic disease were recruited as the control group. For the periodontitis group (n = 20), patients with moderate periodontal disease  [Dental students (grade B)  were carn = 10) stage III periodontitis patients, yielded >95% of measurements within 1 mm of error. Periodontal parameters were recorded at six sites on each tooth using the same probe. These included the following parameters: absence/presence of plaque on tooth surfaces using a dichotomous plaque index, and absence/presence of bleeding on probing, probing pocket depth, and exercise for recession. Clinical attachment level was calculated post hoc from probing pocket depth and exercise for recession. If a peculiar non-periodontal reason for periodontal tissue destruction was suspected , patients were excluded from the final evaluation.After a brief periodontal health and dental pathology interview at the Department of Oral Medicine and Periodontology, University Medical Centre Ljubljana, Slovenia, all patients underwent a comprehensive dental and periodontal examination performed by a single experienced examiner. Using the Williams periodontal probe , a calibration exercise for recession and probing pocket depth, including ten . Furthermore, the principles outlined in the revised Declaration of Helsinki on experiments with human participants were followed.All subjects received detailed verbal and written instructions regarding saliva and dental plaque sample collection. These included not coughing or clearing their throat into the collection tube and abstaining from eating, tooth brushing, using a mouthwash, drinking alcohol, taking drugs, or smoking for 1 h prior to saliva collection. The mouth was rinsed with tap water a few min before saliva collection. Unstimulated saliva was collected into a sterile 15-mL tube until at least 1 mL of saliva was obtained.The same dentist collected all plaque samples. Before sampling, selected teeth with the deepest probing pocket depth in each yaw quadrant were isolated with cotton rolls. The plaque sample was harvested with a sterile Gracey curette with one vertical stroke on the root surface starting from the periodontal pocket/sulcus depth. The working end of the curette was transferred to the sterile container and the visible plaque was wiped off against the wall of the container. Samples were collected from all four sites in each quadrant. In case of contamination of the plaque samples by blood, the samples were discarded and new plaque samples were collected from the second deepest probing pocket of the quadrant.2O and sonicated  on ice for 5 min at 40% amplitude under 2 sec cycles. Total lipids from clinical samples were extracted as previously described for bacteria  were first resuspended in 1 mL of dHbacteria .P. gingivalis, A. actinomycetecomitans, and E. coli (10 µg each sample) were applied on a plate precoated with Silica Gel 60 (HPTLC plate). The plate was dried with a hairdryer and lipids were separated with a mobile phase consisting of chloroform/methanol/25% ammonia (65/25/4 v/v/v). After separation, the plate was dried again and the lipids were blotted to a polyvinylidene difluoride (PVDF) membrane using an iron. Previously, the PVDF membrane was activated for 30 sec in an activation solution . After blotting the PVDF membrane was immersed in 3% bovine serum albumin (BSA) in Tris-buffered saline  for 2 h at 25 °C to block nonspecific binding of the protein. ErylysinA (2 μg/mL) in 3% BSA in TBS was added to the membrane and left to incubate for 2 h at 25 °C. The membrane was washed three times for 10 min in TBS and incubated with anti-His primary antibodies (1:1000) for 1 h at 25 °C. After washing, horseradish peroxide-conjugated anti-mouse IgG antibodies (1:1000) were added and left for 1 h at 25 °C. The membrane was washed three times for 10 min in TBS and the peroxide detection reagent was added. When the colour of the reaction product appeared, the surface of the membrane was washed with water.Commercial lipids  and total lipids extracted from To visualize the separated lipids, the HPTLC plate was sprayed with primulin reagent and the bands were visualized under UV light at 365 nm.2 in size) and placed in a 12-well plate. Lipid extracts from bacteria (20 µg), clinical samples (200 µg), and lipid standards (14 µg CPE and 20 µg SM) were applied directly on individual nitrocellulose membranes and left for 15 min at 25 °C to dry completely. Each well was blotted with blocking buffer (3% milk in TBS) overnight at 4 °C with shaking (200 rpm). The plate was rinsed three times with TBS and incubated with EryA-mCherry . After 2 h of incubation with shaking (200 rpm) in the dark at 25 °C, the plate was washed three times with TBS. Membranes were placed on glass slides, and the interaction of lipid-bound EryA-mCherry was analysed using a stereomicroscope  with a CCD camera at 1.0 × magnification. Images were analysed using the programme FIJI ImageJ. To quantify the binding of EryA-mCherry to lipid extracts from dental plaque, we measured the sum of all pixel intensities across all pixels in an object using ImageJ and an equimolar SM/Chol lipid mixture as a negative control to determine CPE-negative  or CPE-positive individuals .The nitrocellulose membrane  was cut into pieces .P. gingivalis or E. coli, were loaded with calcein in the self-quenching concentration (80 mM), as described previously [Small unilamellar vesicles composed of CPE, POPC, and Chol  or of total lipids extracted from eviously . The persensitivity: the probability that a test result will be positive when the disease is present (true positive rate), specificity (probability that a test result will be negative when the disease is not present (true negative rate)), positive likelihood value (ratio between the probability of a positive test result given the presence of the disease and the probability of a positive test result given the absence of the disease), negative likelihood value (ratio between the probability of a negative test result given the presence of the disease and the probability of a negative test result given the absence of the disease), positive prediction value (probability that the disease is present when the test is positive), negative predictive value (probability that the disease is not present when the test is negative), and accuracy ) were calculated with a prevalence set at 50% (n = 20 in both groups).The results of the dot blot assay of clinical plaque samples were analysed concerning the standard clinical diagnostic procedures to compare both approaches by MedCalc (Version 20.110) statistical software . Standard diagnostic parameters  and total Chol to its lipid composition, with a relative abundance of 29% and 71%, respectively  was almost absent (<1%), PE diagnostic peak  showed their relative abundance to be around 3%. Phosphoethanolamine was found by mass spectrometry to be composed only of branched, fully saturated acyl chains, with the major species PE 30:0 (ca 90%) and PE 28:0 (ca 10%).ectively . We coul1H-NMR or by LC-MS, due to their low abundance. On the other hand, mass analysis revealed the presence of 2′OH-CPE analogues , with the three major species being 2′OH-DH-CPE 35:0 (ca 46 mol%); 2′-hydroxy-CPE (2′OH-CPE) 35:1 (ca 6 mol%); and 2′OH-DH-CPE 36:0 (ca 48 mol%)  . The pre studies ,46.T. forsythia no NMR spectra could be acquired, meaning that inter-class relative abundance of lipid composition could not be obtained. We were able to achieve the lipid intra-class distribution by quantitative HPLC-MS/MS analysis to give a precise estimation of ceramide class abundance over total lipid extract. We focused on MS analysis of CPE analogues, and we could identify four CPE-related classes, bearing different oxidation states at the sphingosine double bond and at the 2′-position on the amidic chain. In particular, we observed canonical CPE; DH-CPE lacking the double bond (position C4-C5) on the sphingosine backbone; 2′-hydroxy-dihydro-CPE (2′OH-DH-CPE); and the 2′-acyl-dihydro-CPE (2′acyl-DH-CPE), that presented a branched acyl chain ) were calculated as the total mass of the lipid class over the total mass of the lipid extract. To obtain a qualitative estimate of the 2′-acyl-DH-CPE, we calculated the ratio of the total MS area of the 2′OH-DH-CPE species to the total MS area of the 2′-acyl-DH-CPE. Note that this was conducted assuming that 2′-acyl- and 2′-hydroxy-DH-CPE have the same ionization response. This gave a ratio of 2′OH-DH-CPE /2′-acyl-DH-CPE of 1.6, indicating that the acyl-DH-CPE concentration is at least of the same order of magnitude as the hydroxy-DH-CPE.To estimate the concentration of CPE, DH-CPE, and 2′OH-DH-CPE, we assumed that their ionization response factor was the same, as determined by a calibration curve with a standard CPE. Unfortunately, the 2′-acyl-DH-CPE class was observed with a different MS setup, so we could not compare the MS data with the standard CPE. Quantitative MS analysis showed relatively low amounts of CPE and DH-CPE and a significant contribution of 2′OH-DH-CPE . The conw/w), with CPE 34:1  and DH-CPE 36:0  accounting for the majority (The most representative species of 2′OH-DH-CPE were found to be: 2′OH-DH-CPE 34:0 (% molar fraction = ca 37%); and 2′OH-DH-CPE 35:0 ca 44%). A complete list of the most abundant Cer with their relative molar distribution can be found in majority . Interes%. A compBesides DH-CPE, we observed other classes of dihydroceramides (DH-C) bearing different polar heads, such as DHC-phosphoglycerol, and DHC-phosphoinositol, as minor membrane components. In these classes, we detected the presence of the same C15 acyl chain at the 2′-position on the amidic chain. Interestingly, the relative distribution of DH-C and their corresponding C15 DH-C-esters followed a similar lipid species distribution, suggesting the acylation of the secondary –OH group as a biochemical process shared by all the 2′-hydroxyl-dihydroceramide classes. Regarding other lipid classes, we found total Chol as both FC (ca 7%) and CE (ca 93%), but we could not establish the lipid/Chol ratio as we had no NMR data available. The CE class was constituted by the major components CE 18:1 (ca 35%); CE 18:2 (ca 29%); and CE 18:3 (ca 20%). Very few species of PC and SM could be detected, suggesting a strongly favoured biosynthesis towards Cer with phosphoethanolamine head, rather than ceramide with phosphocholine head . MS analysis of the free fatty acids (FA) class showed the most abundant species to be FA 18:0 (50%), FA 15:0 (23%), FA 18:1 (11%), and FA 16:0 (9%). It is interesting to notice that the second most abundant FA is the saturated ω-2 methyl C15 acyl chain, which is used upon 2-′acyl-DH-CPE biosynthesis.The role and biophysical properties of dihydrosphingolipids are still enigmatic. What is certain is that in phospholipid–sphingolipid–cholesterol mixtures, DH-C gives rise to more rigid mixtures than the corresponding 4-unsaturated compounds (Cer) . This enSaccharomyces cerevisiae as a critical factor in maintaining membrane fluidity and proper turnover of membrane molecules [Porphyromonas gingivalis and T. forsythia could utilize the modified CPE species to maintain membrane structure and function. On the other hand, other studies report that α-hydroxylation of the N-acyl chain has no significant effects on membrane order, although some relevant effects on the physical properties of pure Cer were observed when these hydroxylated sphingolipids were mixed with certain phospholipid mixtures [The presence of a hydroxyl group at position 2 of the fatty acid is a characteristic feature of the CPE species produced by both bacteria studied. However, the role of such modification of a fatty acid is far from clear and contradictory explanations are found in the available literature. Hydroxylation at position 2 of a fatty acid, associated with a sphingoid base has been implicated in olecules . Porphyrmixtures .As a final consideration, how it has been correctly emphasized in a recent review on the topic , we cannP. gingivalis and T. forsythia, we wanted to further analyse whether commercial CPE and bacterially derived CPE species could be detected with EryA. We had difficulty culturing T. forsythia, which is known for its slow and fastidious growth [As lipidomic analyses showed the presence of CPE species in the total lipid extracts from s growth , so we dP. gingivalis, whereas no binding was detected for lipids from E. coli and A. actinomycetemcomitans , Fusobacteriota, Bdellovibrionota, Myxococcota, Mycoplasmota, and to the class of Alphaproteobacteria of the phyllum Pseudomonadota [Escherichia coli and A. actinomycetemcomitans belong to the class of Gammaproteobacteria of the phyllum Pseudomonadota, for which there are no reports of ceramide synthesis. The weaker immunodetection signal of EryA bound to the CPE of P. gingivalis compared with the signal of EryA bound to commercial CPE is a consequence of the relatively low amounts of CPE species in the lipidome of P. gingivalis .The specificity of EryA interaction with CPE species was first analysed using thin-layer chromatography, followed by transfer of lipids to a PVDF membrane and study of EryA-lipid binding by immunodetection . Lipids comitans B. These monadota . EscheriP. gingivalis and E. coli. Binding of EryA-mCherry was visible on both CPE-containing samples  but was not observed in the case of SM or E. coli  or on vesicles composed of E. coli lipids, again confirming the specific activity of EryA for CPE and the absence of CPE in the E. coli lipid sample.In this study, the membrane-permeabilizing potential of EryA/PlyB was investigated on vesicles prepared from the total lipid extract from hout CPE . The higP. gingivalis lipids is a consequence of the presence of CPE species, which were also identified in lipidomic studies. In addition, EryA was shown not to bind to negative controls containing SM or to lipids from bacterial species other than Bacterioidetes. This suggests that in the case of CPE detection by EryA in biological samples, contamination with blood or vertebrate cells would not affect detection.The combined results obtained by immunoblotting on separated lipids, dot blot, and calcein release assay strongly suggest that the affinity of EryA for lipid vesicles composed of P. gingivalis and a specific interaction between EryA and CPE. Since periodontal disease in Slovenian patients is usually associated with the presence of P. gingivalis [Using the lipidomic approach, we confirmed the presence of CPE species in ngivalis , we alsoP. gingivalis, T. forsythia, P. intermedia) in dysbiotic biofilms belonging to the Bacteroidetes [A. actinomycetemcomitans which has not yet been identified as a CPE-producing bacterial species [To test this hypothesis, 20 dental plaque and saliva samples were collected from healthy individuals and 20 from periodontal patients, and the lipids were isolated. Unfortunately, the amount of lipids isolated from the saliva samples was too low for adequate analysis, so we performed detection of CPE with EryA only for the plaque samples. As the amount of these biological samples was small, the semi-quantitative dot blot assay was used to determine the specificity of EryA for CPE for all samples in a single experiment. We observed the binding of EryA-mCherry to almost all  plaque samples from patients with periodontitis and to 11/20 (55%) plaque samples from healthy individuals . We assuroidetes . There w species ,77,79. S species ,81, someThe statistical analysis clearly shows that a negative dot blot assay confirms the absence of periodontitis. In contrast, a positive dot blot assay means that there is a 50% possibility one indeed has a periodontal disease.Compared to the gold standard clinical diagnostic procedure, this results in a sensitivity of 95%, a specificity of 45%, a positive predictive value of 63%, and a negative predictive value of 90%, giving overall test accuracy of 70% (see P. gingivalis is indeed a CPE-producing bacterial species that can be specifically detected by CPE-sensing EryA. Moreover, CPE-sensing EryA is able to detect CPE not only in commercial CPE-containing vesicles or in lipid extracts from periodontal CPE-producing bacteria P. gingivalis, but also in biological samples presumably containing CPE-producing bacterial species. We show here that aegerolysin EryA can be used in combination with the dot blot technique as a suitable semi-quantitative method to determine the presence of CPE in clinical supragingival plaque samples and to detect periodontal disease. However, due to the low amount of CPE in clinical samples, it is difficult to accurately predict whether someone actually has periodontal disease or not. Our research shows the potential of non-self-lipids as new molecular biomarkers for bacterial-associated diseases. Even more, EryA, in combination with its protein partner PlyB, forms pores in vesicles composed of total lipid extracts from P. gingivalis, suggesting that the protein complex may have antimicrobial activity. Finally, because diagnostic methods for the determination and quantification of non-self lipids, which are present in relatively low amounts, are not yet well established, we propose the further development of lipid-based sensing techniques that would allow a more accurate and sensitive analysis of these non-self lipids as biomarkers for chronic inflammatory diseases. Lipid sensing proteins, especially proteins from the aegerolysin family, therefore have great potential for use as diagnostic tools or biosensors in biomedicine.The results of our study show that


In continuity, we conducted a cross-sectional clinical study in order to confirm our in silico assumptions regarding the HBs-Ag antibodies.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for COVID-19 disease which is known to have a broad clinical spectrum, from asymptomatic to critical presentation leading to death. Many researchers have investigated the factors impacting the course of the disease. Our previous n = 340). All clinical presentations were equally represented. Using an ELISA test, each patient benefited of a serology for the detection and measurement of the anti-HBs specific IgG antibodies. The obtained results allowed determining the different correlations between these antibody titers and the disease severity. The R® software and the MedCalc® software served to calculate the Spearman's coefficient of rank correlation (rho) for the obtained titers per severity group as well as the different other calculations and figure representations.A representative sex- and age-matched sample of patients with confirmed COVID-19 was selected (p = 0.04). High anti-HBs titers were significantly associated with the mild presentation of COVID-19. A significant difference was found between the obtained titers per severity class .A significant positive correlation was found with the anti-HBs titers (rho = 0.107; Our findings demonstrated that anti-HBs titers were significantly higher for patients having mild COVID-19 presentations. We presume that being immunized against the HB may play a protective role in the course of the disease. Our study provided more key elements in understanding the disparity of the clinical spectrum among regions. The emergence and the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for COVID-19, have caused global public health, economic, and social crises . As of 2Corynebacterium diphtheriae, Bordetella pertussis, Hepatitis B (HB), Hepatitis A, Haemophilus influenzae type B (Hib), and Streptococcus pneumoniae vaccines (PCV10)]  identified three segments in Hepatitis B, Measles and Tetanus proteins presented antigenic properties that can induce putative protective effect against SARS-CoV2  and inactivated ones  . A totalARS-CoV2 .in silico study .® LIMS storing application  of Pasteur Institute of Tunis. The included sera were randomly selected from the LCV bio-bank; they were collected during the pandemic from patients with different clinical presentations and then carefully stored in a −40°C freezer in accordance with the BAOBABlication . A totallication . Each grlication  or by SAThe socio-demographic data of patients and information on clinical features, co-morbidities, and exposure or contact history with COVID-19 patients were collected.in vitro diagnostics (IVD)-validated immunoassay: an anti-HBs enzyme immunoassay kit, ETI-AB-AUK-3, manufactured by the DiaSorin® S.p.A., Italy (REF: P001603). This assay is based on a direct and non-competitive sandwich ELISA. It enables detection of anti-HBs IgG-specific antibodies using wells coated with heat-treated human HBs-Ag. The measurement of the anti-HBs specific antibodies depends on the use of standardized calibrators that were referenced against WHO anti-Hepatitis B Immunoglobulin 1st International Reference Preparation, 1977. This kit is recommended for measuring the anti-HBs titers whether acquired as a result of natural HBV infection or after vaccination. The sensitivity and specificity of this kit are 99.11% CI 95% (98.18–99.64%) and 98.21% CI 95% (97.07–99.00%), respectively, following the manufacturer's instructions. The testing procedures and result interpretation were conducted according to the kit instructions: a titer lower than 10 mIU/mL indicates that the patient is not immunized against the HBV; a titer higher than 10 mIU/mL is correlated to an efficient immunity against the virus; however, a titer more than 100 mIU/mL is recommended for the vulnerable populations such as the health care workers. This classification also aligns with the WHO recommendations  and the R® software (version 3.4). A p-value of <0.05 was considered statistically significant.To explore the relationship between anti-HBs specific antibody titers and the severity of COVID-19 cases, the sample size was first calculated with 80% power of the test, an alpha value set to 0.05, and a correlation value of 0.3 using Epitools® . The sam® . The SpeThis study included 340 patients that were stratified according to COVID-19 disease severity into four groups: “asymptomatic,” “mild,” “moderate,” and “severe.” The required sample size was 85 patients in each group. Among the 340 patients, 160 were female (47%) and 180 (53%) were male. The sex ratio male/female (M/F) was estimated at 1.1. The mean age for all groups was 54 years  of patients did not have detectable anti-HBs antibodies. For the remaining proportion of patients who had positive anti-HBs antibodies , it was distributed according to the COVID-19 disease severity group as shown in p = 0.03). In addition, a significant reverse correlation was found between the patients' ages and the obtained anti-HBs antibody titers ; this association demonstrated that higher anti-HBs titers were detected in children and the adult patients than that in older age.All sera were tested for the presence of anti-HBs antibodies. In total, 54.4%  according to the National Institute of Health definitions  (in silico study and we showed that the amino-acid sequence PGTNTSN in the Spike protein of SARS-CoV-2 (position 600–606) matches with the predicted epitope TNTSN in the HBs-Ag-adr (p = 0.04) which is in concordance with our previous in silico findings  , 33. Thes-Ag-adr . The pats-Ag-adr  that twofindings . TherefoRelying on clinical observations, Chen et al.  and Wu ein silico docking evidence suggesting that Lamivudine may bind and possibly work as an inhibitor of the SARS-CoV-2 RdRp RNA polymerase .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The coronavirus disease 2019 (COVID-19) has become a global pandemic. Systemic inflammation in COVID-19 patients has been associated with poor clinical outcome. This study aims to determine the relationship between platelet count and in-hospital mortality.The original data of this study were from article development and validation of a predictive model of in-hospital mortality in COVID-19 patients. In this secondary analysis, we adopted multi-variable logistic regression analyses and smooth curve fitting to assess the independent association between platelet count and in-hospital mortality. We further applied a two-piecewise linear regression model to examine the nonlinear association between platelet count and in-hospital mortality.9/L. On the left side of the inflection point, the OR was 0.996 . On the right side of the inflection point, the OR was 1.011 .Of the 2006 patients, the average age of the participants was 65.9 ± 16.5 years and 42.6% were women. We observed a U-shaped relationship between platelet count and in-hospital mortality. We found two different slopes, the correlations between platelet count and in-hospital mortality of COVID-19 patients were totally different below and above the inflection point which was around 370 × 109/L.A U-shaped association between platelet count and in-hospital mortality was found in the patients with COVID-19. The optimal of platelet count associated with the lowest risk of in-hospital mortality was around 370 × 10 The coronavirus disease 2019 (COVID-19), an infectious disease caused by a novel strain of human coronavirus, has become the focus of attention worldwide . Platelepost-hoc the association of platelet count measured at basement with in-hospital mortality.In the general , COPD 11, venoushttps://journals.plos.org/plosone/s/data-availability), we can use this dataset to perform secondary analysis based on different scientific hypotheses. The original study was granted an exempt status and the requirement for obtaining informed consent was waived by the Ethics Committee for Clinical Research of the Hospital Universitario Fundación Jiménez Díaz , Hospital Infanta Elena , Hospital Universitario Rey Juan Carlos , and Hospital Universitario Fundación Jiménez Díaz in Madrid] from 27 February to 17 April 2020. The diagnosis of COVID-19 was based on World Health Organization interim guidance and confirmed by RNA detection of 2019-nCoV in the clinical laboratory of Hospital Universitario Fundación Jiménez Díaz. Diego et al. extracted de-identified data from the Huawei  platform and the collaboration of Indizen-Scalian . Four patients younger than 18 years old and 60 patients missing platelet count data were excluded in further analysis.Baseline platelet count was first collected either in the emergency department or within 3 days from admission to a ward from electronic medical records .We included the following variables based on published literature and clinical experience: demographic characteristics and chronic comorbidities . Laboratory values included body mass index (BMI), lactate dehydrogenase (LDH), ferritin, D-dimer, absolute lymphocyte count, estimated glomerular filtration rate (eGFR), activated partial thromboplastin time (APTT), and fibrinogen.The outcome was in-hospital mortality which was monitored up to 17 April 2020 .Descriptive analysis was performed for all patients. Categorical variables were expressed as numbers and percentages. Continuous variables were expressed as mean and standard deviation (SD) for normal distributions or median and interquartile range for skewed distributions. We used the chi-square test, one-way ANOVA, and Kruskal–Wallis test for the comparison of categorical, normally distributed, and non-normally distributed continuous variables, respectively. We used dummy variables to indicate missing covariate values .http://www.R-project.org, The R Foundation) and Free Statistics software version 1.3  platelet count group had the lowest in-hospital mortality.The overall in-hospital mortality was 18.7%. 9 /L vs. 100–550 × 109/L vs. >550 × 109/L for sensitivity analysis. Compared with 100–550 × 109 /L groups, the ORs of <100 × 109/L and >550 × 109 / L were 2.34 (1.35–4.07) and 1.69 (0.51–5.6) after adjusting for all covariates in We tried to look at different thresholds to identify patients at risk and used <100 × 10P-value for the non-linear test was 0.037 (9/L (p < 0.001). On the right side of the inflection point, the OR was 1.011 . It suggests that the risk of in-hospital mortality started to decrease by 0.4% per 1 × 109/L platelet change until a platelet count of ~370 × 109/L. Then the risk of in-hospital mortality started to increase by 1.1% per 1 × 109/L platelet change .Through the multivariate logistic regression model and smooth curve fitting, we observed that the relationship between platelet count and in-hospital mortality was non-linear . Data weas 0.037 , we thus037 (9/L . On the P < 0.05).Univariate logistic and multivariable logistic regression analysis of risk factors for in-hospital mortality in patients with COVID-19 is reported in 9/L.We also detected the association between platelet count and ferritin in order to understand the relationship between platelet count and inflammation. Based on 9/L. Platelet count, as assessed at baseline, was negatively associated with in-hospital mortality of COVID-19 patients below 370 × 109/L, and it was positively associated above 370 × 109/L. The optimal platelet count associated with the lowest risk of in-hospital mortality was around 370 × 109/L.In this observational retrospective cohort study, we tried to examine the optimal platelet count associated with in-hospital mortality in patients with COVID-19. A U-shaped association between platelet count and in-hospital mortality was found in the cohort. The correlations between platelet count and in-hospital mortality of COVID-19 patients were totally different below and above the inflection point which was around 370 × 109/L. In a previous study, thrombocytopenia was associated with poor outcome in patients with COVID-19  . This instability may be the result of the highly sensitive smooth curve fitting in analyzing change trends.We used smooth curve fitting  and a twIn fact, a U-shaped association between platelet count and in-hospital mortality is universal in different diseases. Several studies have found a non-linear relationship between platelet count and outcomes. Fawzy et al.  demonstrThe association between platelet count and clinical outcome may not reveal any causality as many parameters could both be the cause and/or the consequence of the changing platelet count. For example, thrombocytopenia could be due to an inflammatory response. The pathophysiology of thrombocytopenia in COVID-19 is hypothetically caused by the alteration of platelet production and consumption (and/or destruction) . It affeSimilar to other studies, we found age , male geOur research has the following limitations that need attention. First, residual confounders potentially exist, as with all retrospective analyses. By maximizing the sample size, we adjusted for all possible confounders we could. Second, our data are only from Spain and cannot cover other populations. Third, the association between platelet count and clinical outcome may not reveal any causality. However, we tried various techniques such as the non-linearity relationship test and used different thresholds group analyses to confirm this relationship which is worthy of further investigation.9/L.A U-shaped association between platelet count and in-hospital mortality was found in patients with COVID-19. The optimal platelet count associated with the lowest risk of in-hospital mortality was around 370 × 10The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants or their legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.QY designed the study and wrote the manuscript. JG conducted data analysis and wrote the manuscript. XZ drew the figures. JC conducted data analysis. DW conducted data interpretation and modified the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Changes in metabolic parameters under resting conditions and during cycle ergometry  from pre- to post-intervention were determined by lactate diagnostics and measurements of the respiratory exchange ratio (RER). Additionally, body composition and perceptual responses to the diets [visual analog scale (VAS)] were measured. A significance level of α = 0.05 was considered. HFLC-G was associated with markedly decreased lactate concentrations during the submaximal  and incremental cycle test  and reduced RER values at rest  during the submaximal  and incremental cycle test . In the HFLC-G, fat mass (p < 0.001) decreased. In LGI-G lactate, concentrations decreased in the incremental cycle test . In the LGI-G, fat mass (p < 0.01) and VAS values decreased, indicating improved levels of gastrointestinal conditions and perception of effort during training. The main findings in the HGI-G were increased RER  and lactate concentrations  at rest. Although the impact on fat oxidation in the LGI-G was not as pronounced as following the HFLC diet, the adaptations in the LGI-G were consistent with an improved metabolic flexibility and additional benefits regarding exercise performance in male athletes.Consuming low glycemic carbohydrates leads to an increased muscle fat utilization and preservation of intramuscular glycogen, which is associated with improved flexibility to metabolize either carbohydrates or fats during endurance exercise. The purpose of this trial was to investigate the effect of a 4-week high fat low carbohydrate (HFLC-G: ≥65% high glycemic carbohydrates per day;  It was shown that the fat oxidation during exercise increased after the consumption of low GI carbohydrates compared to high GI carbohydrates –19. ThisTherefore, the aim of the current pilot study was to examine the impact of a high fat low carbohydrate (HFLC-G) vs. high carbohydrate low glycemic (LGI-G) vs. high carbohydrate high glycemic (HGI-G) diet on metabolic parameters, body composition, and perceptual responses to the diets.The study was designed as a monocentric, prospective, open pilot trial conducted at the University of Freiburg, Germany. In total, 30 healthy male endurance athletes as distance runners, cyclists, and athletes performing basic endurance training  aged between 18 and 50 years were recruited (at least three training sessions per week). The sample size was set on 10 participants per group to obtain information for a power analysis to specify meaningful group differences . ProfessFor all visits, the participants were advised to arrive at the University of Freiburg in the morning at the same time following a fasted period of 12 h. In addition, general guidelines were to drink 1 L of water in the evening and another 0.5 L in the morning before the measurement to ensure euhydration . In addi2, respiratory exchange ratio (RER), and submaximal metabolic inflection points . For this purpose, a breath-by-breath gas analyzer  was used. Capillary blood samples were collected at rest, every 3 min, and at exhaustion and analyzed using Biosen Glucose and Lactate analyzer . Matching for the lactate threshold was used to assign participants to the study groups  to minimize baseline differences in the incremental test results. As the first measurable increase in blood lactate concentration during physical activity, the lactate threshold was automatically evaluated by the computer software . In addition, participants were asked to complete a 3-day nutrition protocol which included 2 weekdays and 1 day of the weekend before the intervention. The protocols were analyzed with Nutriguide . The Freiburg Questionnaire of physical activity was used to protocol frequencies of sports and total time [h/week] of physical and sports activity prior to the intervention , were measured. An incremental cycling test was performed  on a stationary cycloergometer  to determine physiological parameters such as VOrvention .At baseline (T0) and post-intervention (T4), body composition (fat free mass and fat mass) was estimated by using a bioelectric impedance analysis (BIA) with a high reliability for evaluating body composition in healthy adults , 26. Par2 and the RER were used in the following Equation (1) by Weir (The resting energy expenditure (REE) was measured in a quiet, lying position. The actual REE measurement was preceded by a discarded 5-min measuring phase. The respiratory gases were measured for 10 min using the same device from the preliminary incremental cycle test . The mea by Weir  to calcu2) during exercise were calculated by the mean of each minute.To determine submaximal exercise metabolism, participants performed a 10-min submaximal cycle test at 20 W above the lactate threshold, which was individually identified in the preliminary incremental cycle test. Blood samples were collected from the ear lobe at rest and at 5 and 10 min. The lactate and glucose concentrations during exercise were determined as the mean value of 5 and 10 min. Values of gas analysis  to assess the concentrations during the incremental cycle test using the following Equation (2):Ten minutes after completing the submaximal cycle test, an incremental test followed under the same conditions: cycling 3 min at 100 W, then increasing 20 W per 3 min until exhaustion, as described for the screening. For RER, lactate, and glucose values, the area under curve (AUC) was calculated between the start of the test and the final increment completed by all participants before exhaustion  were evaluated using a visual analog scale (VAS), a validated measurement instrument for quantitative assessment between 0  and 100 (“worst condition”). The distance between “optimal condition” and the point marked by the participant is given in mm by the VAS scale .Participants were instructed to follow the dietary pattern according to their respective group over the time course of 4 weeks:HGI-G…≥65% of energy high glycemic (GI > 70) carbohydrates per dayLGI-G…≥65% of energy low glycemic (GI < 50) carbohydrates per dayHFLC-G…≥65% of energy fats, maximum 50 g carbohydrates per daySince the present investigation was conducted as pilot trial, no hierarchy for the efficacy endpoints had been defined in the study protocol. The statistical evaluation was performed to determine an adequate sample size and the primary outcome of a main RCT study which will be designed on the basis of the present study protocol.All data are presented as mean ± standard deviation (SD). Medians (Md) were additionally presented if outliers were identified by the interquartile range method. SPSS statistics  was used for all statistical analyses. All the tests in the descriptive analysis were performed as two-sided tests, and the significance level was set at α = 0.05.post-hoc test was performed to identify the groups that differed significantly. The Kruskal–Wallis test was used when data cannot be assumed to be normally distributed. Following a significant Kruskal–Wallis test, pairwise comparisons using the Dunn-Bonferroni approach were automatically produced. The significance of changes from baseline to post-intervention in the respective endpoints within groups were analyzed with the paired sample t-test or Wilcoxon signed-rank test. As a magnitude of the change in the respective outcomes, the minimally important difference (MID) was calculated. The value of 0.5 SD can serve as the smallest change from baseline to post-intervention that participants perceive as important . The mean height was 1.82 ± 0.08 m for HGI-G, 1.77 ± 0.06 m for LGI-G, and 1.79 ± 0.06 m for HFLC-G with no significant group differences (p = 0.185). Drop outs were whose who had voluntarily withdrawn from participation after the initial examination. No adverse events were noted, and no pathological findings were observed in the routine anamnesis. The analysis of the initial activity protocols revealed no significant differences (p = 0.822) between the HGI-G (7.79 ± 2.65 h/week), LGI-G (7.88 ± 2.83 h/week), and HFLC-G (7.15 ± 2.60 h/week). Endurance running, cycling, team sports, and cross-country skiing were the main reported activities in all groups.A total of 30 men met the inclusion criteria and were allocated to the intervention groups . Twenty-p < 0.01) in all study groups. A statistically significant increase in protein intake could be observed in the LGI-G and HFLC-G (p < 0.001). Furthermore, the glycemic index of the consumed foods decreased statistically significantly (p < 0.001) in the LGI-G and increased statistically significantly (p < 0.001) in the HGI-G during the intervention (p = 0.887). The carbohydrate and fat intake differed statistically significantly between groups (p < 0.001). Moreover, the analysis of the nutritional protocols revealed a statistically significantly lower glycemic index in the LGI-G compared with the HGI-G during the intervention (p < 0.001). The daily intake of carbohydrates was higher in the HGI-G than in the LGI-G, with no group differences for the absolute (p = 0.979) or percentage (p = 0.981) carbohydrate intake. Referring to the body weight, the LGI-G had even a higher carbohydrate intake than the HGI-G, with no statistically significant group difference (p = 0.514). The fat intake of the HFLC-G was statistically different from the HGI-G (p < 0.001) and the LGI-G (p < 0.001). The protein intake also differed significantly between groups (p < 0.001). The post-hoc analysis revealed a statistically significant higher (p < 0.001) protein intake (percent of energy) in the HFLC-G compared with the HGI-G. The average percentage of protein intake of the LGI-G was statistically significantly (p = 0.029) lower than in the HFLC-G, with a tendency toward a significance (p = 0.057) higher than in the HGI-G. Taking the body weight into account, the protein intake during the intervention was only statistically significantly different between the HGI-G and HFLC-G (p < 0.001).As shown in rvention . There wThe baseline data of the study participants are summarized in p = 0.007, d = 1.508; HFLC-G vs. HGI-G: p < 0.001, d = 2.047) than the HGI-G (0.134 ± 0.473 kg). Similarly, the changes in the percentage fat mass in the LGI-G (−2.14 ± 1.58%) and HFLC-G (−2.62 ± 1.12%) were statistically significantly different  from the changes in the HGI-G (0.178 ± 1.83%). Due to favorable changes in body fat, the increase in percentage fat free mass was also statistically significantly higher  in the LGI-G (1.22 ± 0.974%) and HFLC-G (1.60 ± 0.656%) compared with the HGI-G (−0.167 ± 1.08%). No statistically significant differences were observed when comparing the changes in fat mass or fat free mass between LGI-G and HFLC-G.Based on the results of the BIA measurements, the LGI-G (−1.83 ± 1.19 kg) and HFLC-G (−2.57 ± 1.21 kg) exhibit a statistically significantly greater loss in fat mass (LGI-G vs. HGI-G: p = 0.117). In the LGI-G, the RER at rest changed by −0.026 ± 0.108 (p = 0.475). Data of the HFLC-G revealed a non-significant decrease in RER by −0.058 ± 0.108 (p = 0.146). When comparing the differences in resting RER values between the LGI-G and HFLC-G, the effect was small (d = 0.299). The differences between the HGI-G and the LGI-G (d = 0.765) and the HGI-G and the HFLC-G (d = 1.123) were meaningful.The REE did not change to the level of statistical significance or the MID during the intervention period in any of the groups. In addition, there were no significant differences between the groups. Under resting conditions, the RER increased in the HGI-G by 0.047 ± 0.076 (p = 0.001). In contrast, the HGI-G and LGI-G had no statistically significant changes in the RER values .In accordance with resting conditions, the RER during the submaximal cycle test decreased in the HFLC-G from baseline to post-intervention , resulting in a significant difference between these two groups . The differences between the HGI-G and the HFLC-G (d = 1.064) were also meaningful, but not statistically significant (p = 0.065). After 4 weeks of intervention, the lactate concentrations during activity decreased in the HFLC-G  by more than half of the SD in contrast to the LGI-G  and the HGI-G . Differences between groups were not statistically significant. Except for glucose concentrations under resting conditions in the LGI-G , no statistical or MID relevant changes of the glucose concentrations were observed in any group in the submaximal cycle test.After 4 weeks, the lactate concentrations at rest remained stable in the HFLC-G (−0.001 ± 0.097 mmol/l). The lactate concentrations under resting conditions decreased slightly in the LGI-G (−0.060 ± 0.206 mmol/l) and increased statistically significantly in the HGI-G  in the HFLC-G. Furthermore, post-hoc analysis of the ANOVA revealed statistically significant differences between the HFLC-G and the HGI-G  and the HFLC-G and the LGI-G . After 4 weeks, participants of the HFLC-G had statistically significantly (p = 0.014) lower RER values at exhaustion compared to baseline. In the HGI-G RER, values at maximum effort were similar at post-intervention compared to baseline. The same results could be observed in the LGI-G (p = 0.026). Post-hoc analysis showed that a HFLC diet exhibits a significantly lower RER at exhaustion than the LGI diet . Differences between the HGI-G and the HFLC-G were meaningful (d = 0.974), but did not reach the level of significance (p = 0.128).As shown in he LGI-G . As a rep = 0.012] and the HFLC-G  had a statistically significant decrease in AUC for lactate concentrations during the incremental cycle test (d = 1.057) between the HGI-G and the HFLC-G. Nevertheless, the changes in lactate concentration at exhaustion did not differ significantly between groups in contrast to the time to exhaustion (TTE) (p = 0.067) and HGI-G , whereas participants of the HFLC-G  had a statistically significantly lower TTE after 4 weeks of intervention, resulting in statistically significant differences compared to the LGI-G  and HGI-G .Participants of the LGI-G  and the HFLC-G [−86.9 ± 191.1 (mg/dl) × min], but reached only in the LGI-G the level of statistical significance (= 0.023) . Glucosep = 0.008, d = 0.899) and VAS subscale ‘gastrointestinal' . For all other analyses, no statistical or meaningful differences between week 1 and 4 could be detected in the respective group. Except for the VAS subscale ‘activity' (p = 0.012), the Kruskal–Wallis test showed no statistical group differences for the different VAS values. Post-hoc analysis revealed a statistically significant difference between the LGI-G and HFLC-G  and the HGI-G and HFLC-G .Changes in the VAS Score are shown in The main purpose of the present investigation was to examine the effect of nutrition strategies varying in amount and type of carbohydrates on metabolic processes under resting conditions and different exercise scenarios. Compared to baseline levels, lactate concentrations under resting conditions and in submaximal test settings decreased in the group consuming low glycemic carbohydrates in a period of 4 weeks. During the incremental test, changes in lactate concentration were statistically significant and metabolically relevant. Although the fat oxidation was not measured directly in the current investigation, evidence suggests that there is a strong inverse relationship between plasma concentrations of lactate, free fatty acids, and β-oxidation during exercise . As a poIn the last decades, several studies have investigated the metabolic adaptations by long-term ≥2 weeks) HFLC diets. Various investigations (≥2 weeks) have identified an increased utilization of fats measured by decreased RER and lactate values and an increased fat oxidation during resting and submaximal exercise conditions , 32–36.  weeks HFIt has to be mentioned that in most studies, the carbohydrate-rich controls have been defined by the amount but not the GI of the ingested carbohydrates. The consumption of low glycemic carbohydrates is characterized by reduced postprandial glucose concentrations, which stimulates less insulin release. Consequently, the associated effects in the carbohydrate and fat metabolism, such as reduced lactate concentrations, decreased RER values, and increased use of free fatty acids, could be identified despite a high amount of carbohydrates –17, 19. To our best knowledge, there is little evidence coming from studies that have focused on longer-term low GI diets. In a study by Hamzah et al. the effect of the GI of high carbohydrate diets on energy metabolism and running capacity have been investigated . The autThe LGI intervention seemed to have a smaller impact on metabolic adaptations than the HFLC diet. The up-regulating signals of fat oxidation are low insulin concentration and increased concentrations in plasma free fatty acids , 3. A diThe nutritional impact on fat metabolism might also be reflected by the circulating glucose concentrations. Fasting glucose plasma concentrations dropped in the LGI-G to a significant and MID relevant extent. Changes in the HFLC-G seemed to be less pronounced, potentially as a consequence of relatively low baseline values compared to the other groups. During the post-intervention, incremental test glucose concentrations are lower at the same exercise intensity as in the unconditioned  state in both LGI-G and HFLC-G. This is probably related to a stimulation of fat oxidation under resting conditions and during exercise .The results of the HGI-G seemed to be controversial. The increased RER at rest in the HGI-G indicates an elevated metabolization of carbohydrates under resting conditions. In addition, the lactate concentration increase was clinically relevant under pre-exercise condition. Despite increased lactate concentrations during the incremental test, it seems that there is an improved fat metabolism -decreased glucose and lactate values- in the submaximal cycle test. It had previously been described that carbohydrates prior to exercise appear to be beneficial to performance . Hence, The current investigation also observed an improvement in body composition due to a decrease in fat mass following the 4-week LGI or HFLC diet on the level of significance and MID. It is not assumed that the present results can be attributed to the differences in energy intake between groups. Despite the significant difference in proportions of nutrients, the mean energy intake was equivalent between groups with an energy add-on of 100 kcal in the HFLC-G. According to the findings of Hall et al., the additional daily energy intake needs to amount to about 215 kcal (900 kJ) to induce weight gain .There is evidence that athletes can improve their body composition by a high fat (in particular ketogenic) diet –44. Low Despite an improvement in fat metabolism and body composition, there is a growing body of evidence that these changes induced by ketogenic or non-ketogenic HFLC diets are not in association with improved endurance performance, aerobic capacity and peak performance in particular , 50, 51,Furthermore, HFLC diets seem to be impractical and accompanied by side effects that include fatigue, headaches, poor concentration, lethargy, gastrointestinal discomfort, nausea, and unintentional weight loss. One reason might be an insufficient proliferation of essential micronutrients and fibers and glycogen depletion which might be a cause of impaired concentration and hence the neuromuscular connection , 52.The values of the VAS scores of all categories decreased in all groups, indicating that the participants got familiar with the respective dietary concepts. In general, none of the groups experienced clinically relevant elevated VAS scores. Mild symptoms can be defined by a score of 5 to 45 mm on the VAS . This miHowever, only the LGI-G and HGI-G have shown an improvement in VAS scores of the subscale activity and gastrointestinal comfort on a statistical or MID level with a superior effect in the LGI-G. During the last week of intervention, the HFLC-G had statistically significant higher VAS scores in the subscale ‘activity' compared with the LGI-G or HGI-G. These results might be associated with impaired training sessions in the HFLC-G since higher intensity levels could not be reached without the provision of carbohydrates . FurtherIt can be assumed that the present results can be attributed to the implementation of nutritional patterns. According to the analysis of the nutritional protocols, the participants' dietary intake reflected the specified intake of carbohydrates and fats in the respective group. While the HGI-G had a higher percent and total carbohydrate intake, the LGI-G showed a higher carbohydrate intake on a g-per-kg-body-weight basis. The current guidelines for endurance athletes during training on the competition level are 6–10 g carbohydrates per kg body weight and day. These recommendations do not address the GI of the ingested carbohydrates . The par2 are overestimated by a step compared to a ramp incremental test . The patients/participants provided their written informed consent to participate in this study.DZ, HF, AG, and DK designed the study. DZ, HF, and DK were responsible for data acquisition and performed the analysis. All authors read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.